Create an object of class profileCGH

Description

Create an object of class profileCGH.

Usage

as.profileCGH(object,...)
## S3 method for class 'data.frame'
as.profileCGH(object, infaction=c("value","empty"),
value=20, keepSmoothing=FALSE, ...)

Arguments

Details

The data.frame to be convert must at least contain the following fields: LogRatio, PosOrder, and Chromosome. If the field Chromosome is of mode character, it is automatically converted into a numeric vector (see ChrNumeric); a field ChromosomeChar contains the character labels. The data.frame to be converted into a profileCGH objet is split into two data.frame: profileValuesNA contains the rows for which there is at least a missing value for either LogRatio, PosOrder or Chromosome; profileValues contains the remaining rows.

Value

Note

People interested in tools dealing with array CGH analysis can visit our web-page http://bioinfo.curie.fr.

Author(s)

Philippe Hupé, glad@curie.fr

See Also

as.data.frame.profileCGH

Examples

data(snijders)

### Creation of "profileCGH" object
profileCGH <- as.profileCGH(gm13330)

attributes(profileCGH)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(GLAD)

######################################################################################

Have fun with GLAD

For smoothing it is possible to use either
the AWS algorithm (Polzehl and Spokoiny, 2002,
or the HaarSeg algorithm (Ben-Yaacov and Eldar, Bioinformatics,  2008,

If you use the package with AWS, please cite:
Hupe et al. (Bioinformatics, 2004, and Polzehl and Spokoiny (2002,

If you use the package with HaarSeg, please cite:
Hupe et al. (Bioinformatics, 2004, and (Ben-Yaacov and Eldar, Bioinformatics, 2008,

For fast computation it is recommanded to use
the daglad function with smoothfunc=haarseg

######################################################################################

New options are available in daglad: see help for details.

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/GLAD/as.profileCGH.Rd_%03d_medium.png", width=480, height=480)
> ### Name: as.profileCGH
> ### Title: Create an object of class profileCGH
> ### Aliases: as.profileCGH as.profileCGH.data.frame
> ### Keywords: manip
> 
> ### ** Examples
> 
> 
> data(snijders)
> 
> ### Creation of "profileCGH" object
> profileCGH <- as.profileCGH(gm13330)
> 
> attributes(profileCGH)
$names
[1] "profileValues"   "profileValuesNA"

$class
[1] "profileCGH"

> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>